AWS Compute Blog

Tag: AWS Lambda

Introducing self-managed Amazon S3 buckets for AWS Lambda function code

If you manage Lambda functions at scale, you’ve likely hit the 75 GB code storage limit or explained to your security team why deployment artifacts live in an S3 bucket you don’t control. Today, we’re announcing self-managed Amazon S3 buckets for AWS Lambda deployment packages. Lambda reads your code directly from your bucket, eliminating quota […]

Eliminating Java cold starts with AWS Lambda Managed Instances

A single cold start can push your Java Lambda function’s response time from milliseconds to seconds, enough to violate your p99 SLA, timeout a downstream service, and page your on-call. The Java Virtual Machine (JVM) performs best in long-running processes. Its Just-In-Time (JIT) compiler progressively optimizes code over thousands of invocations. Standard serverless execution environments […]

Secure code execution for AI agents with AWS Lambda MicroVMs

Development teams building serverless applications with AI coding agents face the question of how to let those agents generate and execute code without losing control over governance. Agent-generated code needs a secure environment to execute, isolated from production systems and the developer’s local environment. Addressing this requires three things working together: a secure execution sandbox, […]

Build reliable voice analytics workflows with AWS Lambda durable functions and Amazon Bedrock

Contact centers handle millions of voice interactions monthly, but transforming raw call recordings into actionable insights remains a manual and fragile process. With voice analytics workflows, you can decrease the average handle time of a voice call from minutes to seconds and increase the efficiency and productivity of your support agents. Today, these workflows often […]

Modernizing Lambda + S3 workloads with Amazon S3 Files

Learn how Amazon S3 Files simplifies Lambda functions by eliminating transfer code and /tmp constraints. See three modernization patterns with code examples for image processing, ETL pipelines, and multi-agent AI workloads. AWS Lambda functions that interact with Amazon Simple Storage Service (Amazon S3) typically follow a familiar pattern: download an object to /tmp, process it […]

Integrating Event Source Mappings with AWS Lambda tenant isolation mode

Building event-driven multi-tenant SaaS applications typically requires compute isolation between tenants to prevent data leakage, maintain security boundaries, and ensure compliance. Traditionally, you had to choose between two approaches: sharing execution environments across tenants (risking cross-tenant contamination of in-memory state) or managing separate Lambda functions per tenant (which introduces operational overhead, increasing costs, and complicating […]

Building Memory-Intensive Apps with AWS Lambda Managed Instances

Building memory-intensive applications with AWS Lambda just got easier. AWS Lambda Managed Instances gives you up to 32 GB of memory—3x more than standard AWS Lambda—while maintaining the serverless experience you know. Modern applications increasingly require substantial memory resources to process large datasets, perform complex analytics, and deliver real-time insights for use cases such as […]

.NET 10 runtime now available in AWS Lambda

Amazon Web Services (AWS) Lambda now supports .NET 10 as both a managed runtime and base container image. .NET is a popular language for building serverless applications. Developers can now use the new features and enhancements in .NET when creating serverless applications on Lambda. This includes support for file-based apps to streamline your projects by implementing functions using just a single file.

Improving throughput of serverless streaming workloads for Kafka

Event-driven applications often need to process data in real-time. When you use AWS Lambda to process records from Apache Kafka topics, you frequently encounter two typical requirements: you need to process very high volumes of records in close to real-time, and you want your consumers to have the ability to scale rapidly to handle traffic spikes. Achieving both necessitates understanding how Lambda consumes Kafka streams, where the potential bottlenecks are, and how to optimize configurations for high throughput and best performance.

AWS Lambda now supports Java 17

This post was written by Mark Sailes, Senior Specialist Solutions Architect, Serverless. You can now develop AWS Lambda functions with the Amazon Corretto distribution of Java 17. This version of Corretto comes with long-term support (LTS), which means it will receive updates and bug fixes for an extended period, providing stability and reliability to developers […]